A typical computer-supported search returns a list of hits, ranked and ordered, based on the particular search query. In addition, the search result often includes other information, such as links and descriptive summaries. This type of search is generally appropriate for textual content. For example, a search of textual content can be performed through an Internet search engine to obtain a list of text hits ranked according to specific criteria specified by the user and the search engine. Similarly, an online library service search may be performed to obtain a list of articles or books, which may be ranked and ordered according to their similarity to the text in the search query.
Similar searching techniques can also be applied to search video and image content. For example, a search of videos or images can be performed to obtain a list of videos or images matching the search criteria. The videos in a video search can be rendered with an image of a single frame or a short segment for each video. The user can identify the desired video based on the image rendered for that video. Moreover, the images in an image search can be rendered as a grid of thumbnails. Here, the user can identify the desired image based on the thumbnail associated with that image.
Audio files can also be searched in a similar way. For example, audio files can be searched based on a text query to help a user identify relevant audio files. The text query can match with content of the audio file, or some metadata associated with the audio file, such as a participant's name, a subject, a date, or a tag. Here, the search can produce a list or table of audio files ranked and ordered by relevance. The user can then identify the audio files based on the text description. The user can also listen to the audio in an audio file from the search results to help identify the audio file. To listen to the audio in an audio file, the user must click or select the audio file to activate it and initiate audio playback. However, this process can be terribly inefficient, as users have to play each audio file separately to listen to the audio in the file. Yet users may often have to listen to an audio file to be able to correctly identify the audio file. Thus, searching the audio files based on a textual query often does not allow the user to sufficiently identify the desired audio file. However, as the number of audio files to search increases, the process of playing and listening to each audio file separately can become significantly onerous.